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Institution

Universiti Teknologi Malaysia

EducationJohor Bahru, Malaysia
About: Universiti Teknologi Malaysia is a education organization based out in Johor Bahru, Malaysia. It is known for research contribution in the topics: Membrane & Adsorption. The organization has 21644 authors who have published 39500 publications receiving 520635 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors reviewed primary issues regarding the drivers and specific benefits of hybrid renewable energy systems (HRES) and discussed the various renewable energy sources which can be explored for HRES implementation.
Abstract: A hybrid power system is an emerging power generation technique which involves a combination of different energy systems, mostly renewables for optimal output configuration. In modern pursuit for renewable energy (RE) development, optimum conditions for the production and utilization of energy system are considered to be an indispensable feature for economic load dispatch. This is a rationalizing fact taking into consideration the rising price of energy for socio-economic development. Therefore, this paper reviews primary issues regarding the drivers and specific benefits of hybrid renewable energy systems (HRES). Moreover, this paper presents discussions on the various renewable energy sources which can be explored for HRES implementation. Finally, the framework unfolds a vivid review on factors to be considered for designing and implementation of HRES in general including simulation and optimization software packages for making such analyses.

159 citations

Journal ArticleDOI
TL;DR: In this paper, a graphene oxide-magnetic iron oxide nanoparticles (GO-MNP) was synthesized using sonomechanical technique and used as effective adsorbent for synthetic methylene blue (MB) dye removal.
Abstract: Adsorption is one of the most effective methods for the treatment of wastewater containing dyes owing to its low operating cost, simplicity of process design and smaller amounts of harmful substances. In this work, graphene oxide- magnetic iron oxide nanoparticles (GO-MNP) was synthesized using sonomechanical technique and used as effective adsorbent for synthetic methylene blue (MB) dye removal. Batch adsorption experiments were performed with the variation of initial MB dye concentration, pH solution, adsorbent dosage and contact time. The adsorbent showed significant removal efficiency around 99.6% for MB. It was found that the removal rate of MB dye in the solution was higher when higher pH, larger dosage of adsorbent in solution and longer contact time were used. A regenerative study was carried out and minor reduction in adsorption capacity of the regenerated GO-MNP was observed after 2 cycles. Analysis of adsorption equilibrium revealed that the data is well fitted with Langmuir and Freundlich adsorption isotherm model (R2 > 0.97), indicating multi layer adsorption of dye on the surface of adsorbent. In the case of adsorption kinetics, the GO-MNP adsorbent follows pseudo-second order kinetics model showing R2 > 0.999, whereas for pseudo-first order kinetics model, the value of R2 was significantly lower. The finding of the present work highlights simple fabrication of magnetic GO and its application as efficient and magnetically separable adsorbent for environmental clean-up.

158 citations

Journal ArticleDOI
TL;DR: This paper intends to review the developments in water quality monitoring technologies for the detection of biological and chemical contaminants in accordance with instrumental limitations and focuses on the most recently developed techniques for water contaminant detection applications.
Abstract: Water monitoring technologies are widely used for contaminants detection in wide variety of water ecology applications such as water treatment plant and water distribution system. A tremendous amount of research has been conducted over the past decades to develop robust and efficient techniques of contaminants detection with minimum operating cost and energy. Recent developments in spectroscopic techniques and biosensor approach have improved the detection sensitivities, quantitatively and qualitatively. The availability of in-situ measurements and multiple detection analyses has expanded the water monitoring applications in various advanced techniques including successful establishment in hand-held sensing devices which improves portability in real-time basis for the detection of contaminant, such as microorganisms, pesticides, heavy metal ions, inorganic and organic components. This paper intends to review the developments in water quality monitoring technologies for the detection of biological and chemical contaminants in accordance with instrumental limitations. Particularly, this review focuses on the most recently developed techniques for water contaminant detection applications. Several recommendations and prospective views on the developments in water quality assessments will also be included.

158 citations

Journal ArticleDOI
TL;DR: In this article, an optimization model for design and planning of a multi-period, multi-product closed-loop supply chain with carbon footprint consideration under two different uncertainties is proposed, where demand and returns uncertainties are considered by means of multiple scenarios and uncertainty of carbon emissions due to supply chain related activities are considered using robust optimization approach.
Abstract: Climate change and greenhouse gases emissions have caused countries to implement various carbon regulatory mechanisms in some industrial sectors around the globe to curb carbon emissions. One effective method to reduce industry environmental footprint is the use of a closed-loop supply chain (CLSC). The decision concerning the design and planning of an optimal network of the CLSC plays a vital role in determining the total carbon footprint across the supply chain and also the total cost. In this context, this research proposes an optimization model for design and planning a multi-period, multi-product CLSC with carbon footprint consideration under two different uncertainties. The demand and returns uncertainties are considered by means of multiple scenarios and uncertainty of carbon emissions due to supply chain related activities are considered by means of bounded box set and solve using robust optimization approach. The model extends further to investigate the impact of different carbon policies such as including strict carbon cap, carbon tax, carbon cap-and-trade, and carbon offset on the supply chain strategic and operational decisions. The model captures trade-offs that exist among supply chain total cost and carbon emissions. Also, the proposed model optimizes both supply chain total cost and carbon emissions across the supply chain activities. The numerical results reveal some insightful observations with respect to CLSC strategic design decisions and carbon emissions under various carbon policies and at the end we highlighted some managerial insights.

158 citations

Journal ArticleDOI
TL;DR: The study contributes to retailing management by enabling it to implement effective retail segmentation and cross-channel strategy according to CDMS.

158 citations


Authors

Showing all 21852 results

NameH-indexPapersCitations
Xin Li114277871389
Muhammad Imran94305351728
Ahmad Fauzi Ismail93135740853
Bin Tean Teh9247133359
Muhammad Farooq92134137533
M. A. Shah9258337099
Takeshi Matsuura8554026188
Peter Willett7647929037
Peter C. Searson7437421806
Ozgur Kisi7347819433
Imran Ali7230019878
S.M. Sapuan7071319175
Peter J. Fleming6652924395
Mohammad Jawaid6550319471
Muhammad Tahir65163623892
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202371
2022347
20212,812
20203,003
20193,148
20182,980